added example for how to use the flag helper (#256)

Author: LTluttmann

examples/simple/flag.py

@@ -0,0 +1,59 @@
+from dataclasses import dataclass
+
+from simple_parsing import ArgumentParser
+from simple_parsing.helpers import flag
+
+
+def parse(cls, args: str = ""):
+    """Removes some boilerplate code from the examples."""
+    parser = ArgumentParser()  # Create an argument parser
+    parser.add_arguments(cls, dest="hparams")  # add arguments for the dataclass
+    ns = parser.parse_args(args.split())  # parse the given `args`
+    return ns.hparams
+
+
+@dataclass
+class HParams:
+    """Set of options for the training of a Model."""
+
+    num_layers: int = 4
+    num_units: int = 64
+    optimizer: str = "ADAM"
+    learning_rate: float = 0.001
+    train: bool = flag(default=True, negative_prefix="--no-")
+
+
+# Example 1 using default flag, i.e. train set to True
+args = parse(HParams)
+
+print(args)
+expected = """
+HParams(num_layers=4, num_units=64, optimizer='ADAM', learning_rate=0.001, train=True)
+"""
+
+# Example 2 using the flags negative prefix
+assert parse(HParams, "--no-train") == HParams(train=False)
+
+
+# showing what --help outputs 
+parser = ArgumentParser()  # Create an argument parser
+parser.add_arguments(HParams, dest="hparams")  # add arguments for the dataclass
+parser.print_help()
+expected += """
+usage: flag.py [-h] [--num_layers int] [--num_units int] [--optimizer str]
+               [--learning_rate float] [--train bool]
+
+optional arguments:
+  -h, --help            show this help message and exit
+
+HParams ['hparams']:
+  Set of options for the training of a Model.
+
+  --num_layers int      (default: 4)
+  --num_units int       (default: 64)
+  --optimizer str       (default: ADAM)
+  --learning_rate float
+                        (default: 0.001)
+  --train bool, --no-train bool
+                        (default: True)
+"""